**Projection pursuit** is a technique for exploratory data analysis
with emphasis on visualization. It is based on finding low-dimensional
projections of multivariate data that show highly nongaussian distributions.
Projection pursuit is technically very closely related to ICA.

**The FastICA algorithm** is a computationally highly efficient
method for performing the estimation of ICA. It uses a fixed-point iteration scheme that has been found in independent experiments
to be 10-100 times faster than conventional gradient
descent methods for ICA. Another advantage of the FastICA algorithm
is that it can be used to perform projection pursuit as well, thus providing
a general-purpose data analysis method that can be used both in an exploratory
fashion and for estimation of independent components (or sources).
Here are some publications on the algorithm.

**The FastICA package** for MATLAB (versions 5 or 4) is program
package with graphical user interface that implements the fixed-point algorithm
for ICA. See the FastICA
home page.

ICA research at Helsinki University of Technology

You are at: CIS → Fixed-point algorithm for ICA

Page maintained by webmaster at cis.hut.fi, last updated Tuesday, 21-Dec-2010 15:55:04 EET